boston_foodmapping

#cleaning the data
#filter food courts whose licsense status is active and VIOLDTTM in 2018.

boston_food <- mayorsfoodcourt %>% filter(str_detect(VIOLDTTM, "2018")) %>% filter(LICSTATUS=="Active") %>% separate(Location, c("lat","long"),",") %>% filter(!is.na(long) & !is.na(lat))

## Warning: Expected 2 pieces. Missing pieces filled with `NA` in 12430 rows
## [31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 92, 145,
## 146, 147, ...].

#covert location into latitude and longtitude. 
boston_food$lat <- as.numeric(gsub("\\(", "", boston_food$lat))
boston_food$long <- as.numeric(gsub(")", "", boston_food$long))
count <- aggregate(data.frame(count = boston_food$businessName), list( value= boston_food$businessName), length)
boston_food <- boston_food[!duplicated(boston_food$businessName), ]
boston_food <- cbind(boston_food, count)
View(boston_food)

#leaflet 

#content <- paste(sep = "<br/>",
                 #boston_food$businessName,
                 #boston_food$Address)



boston.500 <- boston_food[1:500,]
getColor <- function(boston_food) {
  sapply(boston_food$count, function(count) {
  if(count >= 10 & count <20) {
    "orange"
  } else if(count < 10 & count >=1){
    "green"
  } else if( count >=20 & count <100){
    "purple"
  } else if( count >=100 & count <234){
    "red"
  } 
    })
}
icons <- awesomeIcons(
  icon = "coffee",
  iconColor = 'white',
  library = 'ion',
  markerColor = getColor(boston.500)
)

# Show first 500 rows from the boston_food dataset
leaflet(boston.500) %>% addTiles() %>% addAwesomeMarkers(~long, ~lat, icon=icons, popup = ~as.character(businessName),  options = popupOptions(closeButton = FALSE), label = ~as.character(count))%>%  addLegend("bottomright",colors=c("green","orange","purple","red"),labels = c("<10","10~20","20~100",">100"),title = "Violation Counts", opacity = 1) %>%  
  addMeasure(
    position = "bottomleft",
    primaryLengthUnit = "meters",
    primaryAreaUnit = "sqmeters",
    activeColor = "#3D535D",
    completedColor = "#7D4479") %>% addLayersControl(
    overlayGroups = (boston_food$ViolLevel),
    options = layersControlOptions(collapsed = FALSE))

#%>% addProviderTiles(providers$Esri.NatGeoWorldMap)

boston_map<- make_bbox(lat = lat, lon = long, data = boston_food)
boston_map <- get_map(location = boston_map)

## Warning: bounding box given to google - spatial extent only approximate.

## converting bounding box to center/zoom specification. (experimental)

## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=42.313201,-71.086035&zoom=12&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false

severe <- filter(boston_food, count>80)
ggmap(boston_map) + geom_point(data = severe, mapping = aes(x = long, y = lat, color=count), size=3) + scale_colour_gradient(low = "yellow", high = "red")+ geom_label_repel(
    aes(x = long, y = lat, label = businessName),
    data=severe,
    family = 'Times', 
    size = 2, 
    box.padding = 0.08, point.padding = 0.1,
    segment.color = 'grey50')  + ggtitle("Violation counts over 80")